multiple regression

Fast Company has an FC Expert Blog. I do not know who these experts or what their qualifications are. They really are experts in declaring broad predictions, especially from reading few lines of some old academic paper. One of the experts write in their blog (the Fast Company says it is not responsible for their wisdom),

Grit: The Top Predictor of Success

Why do some companies consistently outperform their competition? Why do some people become champions while others fall short? What skills do you need to improve to reach your highest potential?

The experts, it turns out, did not read the details of the paper they quote. Nor do they seem to understand how predictability is measured in statistical terms and what it means. Needless to say they neglect to speak about omitted variable bias and other experimental errors.

What the paper says is grit, a trait defined by the authors, has an incremental R2 of 4%. That is when you add measure of Grit to whatever linear regression model they were building, the predictability of the model increased by 4%.

4%, just 4% increase after all other variables.

To go from here to “The Top Predictor of Success” is ludicrous.

Not just that, even the authors of the paper list severe limitations. The very definition of Grit is amorphous, it is highly correlated with the Big Five traits (classified in Psychology literature) and in their studies the authors measured it based on self-reporting by test participants.

From a study with such severe limitations (I am surprised it was even published), we get sage advice from Fast Company experts,

It doesn’t matter if you’re rich or poor, come from a good neighborhood, have a fancy-pants degree, or are good looking. We all have nearly limitless potential, and the opportunity to seize it is waiting for you.

Let old-school grit and determination serve as the catalyst to achieving your own personal greatness. You don’t need another tech gadget; just the same killer app that has been foundation of success since the beginning of civilization.

The expert has filtered out gaping holes in the original study, ignored effect of lurking variables, generalized a self-reported measurement of students to the entire population and urges us to show grit.

Look at some of the quotes from the news media on companies with a data driven approach to management and business decisions

Applying a complex equation to a basic human-resource problem is pure Google, a company that made using heavy data to drive decisions one of its “Ten Golden Rules” outlined in 2005. (WSJ on Google’s HR plans)

Like Google, Facebook calculated the relevancy and authority of information before deciding to display it to me. The News Feed was shockingly complex — calculating and ranking more than a trillion items per day — and the results were very satisfying. (WSJ on Facebook Newsfeed)

Mr. Donahoe installed an entirely new system to determine which items appear first in a search. It uses a complicated formula that takes into account price and how well an item’s seller ranks in customer satisfaction. (WSJ on eBay)

What could be more baffling than a capitalist corporation that gives away its best services, doesn’t set the prices for the ads that support it, and turns away customers because their ads don’t measure up to its complex formulas? (Wired on Google)

CineMatch, on the other hand, is all math. It matches your viewing and rating history with people who have similar histories. It uses those similar profiles to predict which movies you are likely to enjoy. That’s what these recommendations really are – predictions of which movies you will like. (Netflix movie recommendation)

I am willing to bet that underneath the complexity is a multiple regression model, built with multiple variable and constantly tuned to better future behavior from past actions. Every business collects or has the opportunity to collect significant customer data. Companies like Google and eBay strive to be accurate 99% of the time or more. But building a regression model even with a handful of variables can improve decision making over driving without a dashboard.